如何在tflite模型上应用元数据？

import tensorflow as tf

# 加载一个现有的TFLite模型
converter = tf.lite.TFLiteConverter.from_saved_model(saved_model_dir)

# 创建一个元数据写入器
metadata_writer = tf.lite.MetadataWriter.create_from_converter(converter)

# 添加元数据
input_tensor_metadata = tf.lite.TensorMetadata()
input_tensor_metadata.shape = [1, 224, 224, 3]
input_tensor_metadata.dtype = tf.uint8
input_tensor_metadata.name = "input"

output_tensor_metadata = tf.lite.TensorMetadata()
output_tensor_metadata.shape = [1, 1000]
output_tensor_metadata.dtype = tf.float32
output_tensor_metadata.name = "output"

metadata_writer.set_tensor_metadata([input_tensor_metadata, output_tensor_metadata])

# 转换模型并写入元数据
tflite_model_with_metadata = converter.convert(metadata_writer=metadata_writer)

# 保存带有元数据的TFLite模型
with open('model_with_metadata.tflite', 'wb') as f:
    f.write(tflite_model_with_metadata)